Load model from HuggingFace if model_directory unset in config YAML

- Do not save/load the model to/from disk when model_directory unset
in config.yml
- Add symmetric search default config to cli.py

src/utils/cli.py

@@ -77,14 +77,22 @@ default_config = {
     },
     'search-type':
     {
-        'asymmetric':
+        'symmetric':
+        {
+            'encoder': "sentence-transformers/paraphrase-MiniLM-L6-v2",
+            'cross-encoder': "cross-encoder/ms-marco-MiniLM-L-6-v2",
+            'model_directory': None
+        },
+         'asymmetric':
         {
             'encoder': "sentence-transformers/msmarco-MiniLM-L-6-v3",
-            'cross-encoder': "cross-encoder/ms-marco-MiniLM-L-6-v2"
+            'cross-encoder': "cross-encoder/ms-marco-MiniLM-L-6-v2",
+            'model_directory': None
         },
         'image':
         {
-            'encoder': "clip-ViT-B-32"
+            'encoder': "clip-ViT-B-32",
+            'model_directory': None
         },
     },
     'processor':

src/utils/helpers.py

@@ -39,14 +39,15 @@ def merge_dicts(priority_dict, default_dict):
 def load_model(model_name, model_dir, model_type):
     "Load model from disk or huggingface"
     # Construct model path
-    model_path = join(model_dir, model_name.replace("/", "_"))
+    model_path = join(model_dir, model_name.replace("/", "_")) if model_dir is not None else None
 
     # Load model from model_path if it exists there
-    if resolve_absolute_path(model_path).exists():
+    if model_path is not None and resolve_absolute_path(model_path).exists():
         model = model_type(get_absolute_path(model_path))
     # Else load the model from the model_name
     else:
         model = model_type(model_name)
-        model.save(model_path)
+        if model_path is not None:
+            model.save(model_path)
 
     return model